An Automated Method for the Quantification and Fractal Analysis of Immunostaining

AIMS In tissue counter analysis (TCA) digital images of complex histologic sections are dissected into elements of equal size and shape, and digital information comprising grey level, colour and texture features is calculated for each element. In this study we assessed the feasibility of TCA for the quantitative description of amount and also of distribution of immunostained material. METHODS In a first step, our system was trained for differentiating between background and tissue on the one hand and between immunopositive and so-called other tissue on the other. In a second step, immunostained slides were automatically screened and the procedure was tested for the quantitative description of amount of cytokeratin (CK) and leukocyte common antigen (LCA) immunopositive structures. Additionally, fractal analysis was applied to all cases describing the architectural distribution of immunostained material. RESULTS The procedure yielded reproducible assessments of the relative amounts of immunopositive tissue components when the number and percentage of CK and LCA stained structures was assessed. Furthermore, a reliable classification of immunopositive patterns was found by means of fractal dimensionality. CONCLUSIONS Tissue counter analysis combined with classification trees and fractal analysis is a fully automated and reproducible approach for the quantitative description in immunohistology.